ACM SIGIR Forum
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Automatic web query classification using labeled and unlabeled training data
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Building bridges for web query classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Query enrichment for web-query classification
ACM Transactions on Information Systems (TOIS)
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Context-aware query classification
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A Hidden Topic-Based Framework toward Building Applications with Short Web Documents
IEEE Transactions on Knowledge and Data Engineering
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This paper describes a query classification system for a specialized domain. We take as a case study queries asked to a search engine of an art, cultural and history library and classify them against the library cataloguing categories. We show how click-through links, i.e., the links that a user clicks after submitting a query, can be exploited for extracting information useful to enrich the query as well as for creating the training set for a machine learning based classifier. Moreover, we show how Topic Model can be exploited to further enrich the query with hidden topics induced from the library meta-data. The experimental evaluations show that this system considerably outperforms a matching and ranking classification approach, where queries (and categories) were also enriched with similar information.